暂无分享,去创建一个
Wojciech Zaremba | Oriol Vinyals | Ilya Sutskever | Oriol Vinyals | Ilya Sutskever | Wojciech Zaremba | O. Vinyals | I. Sutskever
[1] John Makhoul,et al. BYBLOS: The BBN continuous speech recognition system , 1987, ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing.
[2] Beatrice Santorini,et al. Building a Large Annotated Corpus of English: The Penn Treebank , 1993, CL.
[3] Hervé Bourlard,et al. Connectionist Speech Recognition: A Hybrid Approach , 1993 .
[4] Steve Renals,et al. THE USE OF RECURRENT NEURAL NETWORKS IN CONTINUOUS SPEECH RECOGNITION , 1996 .
[5] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[6] Herbert Jaeger,et al. Optimization and applications of echo state networks with leaky- integrator neurons , 2007, Neural Networks.
[7] J. Schmidhuber,et al. A Novel Connectionist System for Unconstrained Handwriting Recognition , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[8] Lukás Burget,et al. Recurrent neural network based language model , 2010, INTERSPEECH.
[9] Holger Schwenk,et al. LIUM’s SMT Machine Translation Systems for WMT 2011 , 2012, WMT@NAACL-HLT.
[10] Lukás Burget,et al. Strategies for training large scale neural network language models , 2011, 2011 IEEE Workshop on Automatic Speech Recognition & Understanding.
[11] Vysoké Učení,et al. Statistical Language Models Based on Neural Networks , 2012 .
[12] Geoffrey Zweig,et al. Context dependent recurrent neural network language model , 2012, 2012 IEEE Spoken Language Technology Workshop (SLT).
[13] Hermann Ney,et al. LSTM Neural Networks for Language Modeling , 2012, INTERSPEECH.
[14] Quoc V. Le,et al. Exploiting Similarities among Languages for Machine Translation , 2013, ArXiv.
[15] Yann LeCun,et al. Regularization of Neural Networks using DropConnect , 2013, ICML.
[16] Geoffrey E. Hinton,et al. Speech recognition with deep recurrent neural networks , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[17] Maneesh Sahani,et al. Regularization and nonlinearities for neural language models: when are they needed? , 2013, ArXiv.
[18] Nitish Srivastava,et al. Improving Neural Networks with Dropout , 2013 .
[19] Alex Graves,et al. Generating Sequences With Recurrent Neural Networks , 2013, ArXiv.
[20] Phil Blunsom,et al. Recurrent Continuous Translation Models , 2013, EMNLP.
[21] Christopher D. Manning,et al. Fast dropout training , 2013, ICML.
[22] Richard M. Schwartz,et al. Fast and Robust Neural Network Joint Models for Statistical Machine Translation , 2014, ACL.
[23] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[24] Wei-Chen Cheng,et al. Language modeling with sum-product networks , 2014, INTERSPEECH.
[25] Razvan Pascanu,et al. How to Construct Deep Recurrent Neural Networks , 2013, ICLR.
[26] Jürgen Schmidhuber,et al. A Clockwork RNN , 2014, ICML.
[27] Pietro Perona,et al. Microsoft COCO: Common Objects in Context , 2014, ECCV.
[28] Georg Heigold,et al. Sequence discriminative distributed training of long short-term memory recurrent neural networks , 2014, INTERSPEECH.
[29] Christian Osendorfer,et al. On Fast Dropout and its Applicability to Recurrent Networks , 2013, ICLR.
[30] Christopher Kermorvant,et al. Dropout Improves Recurrent Neural Networks for Handwriting Recognition , 2013, 2014 14th International Conference on Frontiers in Handwriting Recognition.
[31] Quoc V. Le,et al. Sequence to Sequence Learning with Neural Networks , 2014, NIPS.
[32] Samy Bengio,et al. Show and tell: A neural image caption generator , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).